Date of Award

Spring 1992

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

Committee Director

Stewart Shen

Committee Member

Meng-Sang Chew

Committee Member

Michael Overstreet

Committee Member

Christian Wild

Committee Member

Nageswara Rao

Abstract

Since the first attempts to integrate AI technology and engineering design nearly two decades ago, few expert systems have been shown to demonstrate sufficient reasoning capabilities to solve real-world design problems. The complex nature of design, the lack of understanding of the design process, and the limitations of current expert system technology have all been shown to have adverse effects on the maturity of this research area. Therefore, our direction in this research concentrates on understanding the design process, investigating a novel area of research focusing on creative design, and incorporating the results into a system model feasible for production use. The model presented is based on the concept of reusing past experience and existing cases to solve future design problems in different application domains. The resulting system performs its task by reasoning and learning by ANALOGY while utilizing the Logical-Building Block approach to design. Our method demonstrates the use of a case-based reasoner in conjunction with other existing techniques, such as heuristic reasoning and first principle reasoning, to produce a system with three levels of reasoning strategies. Such a system will exhibit a learning capability by which its performance is enhanced with repeated use. A prototype has been implemented and tested for the synthesis of various mechanisms.

DOI

10.25777/3x59-6c25

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